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In the 10th Minitab tutorial, we are in the shockpad production of Smartboard Company. Shockpads are plastic plates, that are installed between the skateboard deck and the Axles. They are primarily used to absorb vibrations and shocks while riding. High-priced designer shockpads are currently being produced for a very discerning customer. The rectangular shockpads are manufactured in series production in a stamping process from high-priced polyurethane panels, specially produced for the customer. A punching batch always consists of 500 shockpads and corresponds to a delivery batch. In contrast to other customers, the customer also attaches great importance to the visual appearance of the shockpads. Therefore, the possible defects, scratches, cracks, uneven cut edges and punching cracks, in the punching process must be avoided. As according to the contractual customer-supplier agreement, surface defects are only permitted up to a certain number. Specifically, according to the contractual complaint’s agreement for Smartboard Company, there is a restriction, that each packaging unit consisting of 500 shockpads may contain a maximum total of 25 defects, the distribution of defects in the delivery is irrelevant. The basic defect rate per delivery, which must not be exceeded, is 5%. The central topic in this Minitab tutorial will therefore be to make a 95% reliable statement regarding the actual defect rate in the population of shockpad production on the basis of an existing sample data set. We will learn that hypothesis tests that follow the laws of the so-called, Poisson distribution, can be used in such cases. We will be able to distinguish the difference between total occurrences, and defect rate, and also become more familiar with the Poisson distribution using the associated density function, to gain insight into the normal approximation associated with the Poisson distribution. We will also learn about useful options such as the sum and tally functions. With the knowledge gained, we will then be able to properly perform the corresponding hypothesis test, on total occurrences of Poisson distributed data, in order to be able to make 95% confident statements, about the total occurrences or defect rates in the population of the punching process.


  • Total Occurrences and defect rates of poisson distributed data
  • Graphical derivation of the Poisson distribution
  • Interpreting the probability density of the Poisson distribution
  • Normal approximation in the context with the Poisson distribution
  • Determine total occurrences in Poisson distribution
  • Hypothesis definitions for poisson distributed data
  • Working with the sum function in the context of the Poisson distribution
  • Working with the function “tally individual variables” in the context of Poisson distribution